A systematic review of behaviour change interventions to improve maternal health outcomes in sub-Saharan Africa

The rate of decline in the global burden of avoidable maternal deaths has stagnated and remains an issue of concern in many sub-Saharan Africa countries. As per the most recent evidence, an average maternal mortality ratio (MMR) of 223 deaths per 100,000 live births has been estimated globally, with sub-Saharan Africa’s average MMR at 536 per 100,000 live births—more than twice the global average. Despite the high MMR, there is variation in MMR between and within sub-Saharan Africa countries. Differences in the behaviour of those accessing and/or delivering maternal healthcare may explain variations in outcomes and provide a basis for quality improvement in health systems. There is a gap in describing the landscape of interventions aimed at modifying the behaviours of those accessing and delivering maternal healthcare for improving maternal health outcomes in sub-Saharan Africa. Our objective was to extract and synthesise the target behaviours, component behaviour change strategies and outcomes of behaviour change interventions for improving maternal health outcomes in sub-Saharan Africa. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Our protocol was published a priori on PROSPERO (registration number CRD42022315130). We searched ten electronic databases (PsycINFO, Cochrane Database of Systematic Reviews, International Bibliography of Social Sciences, EMBASE, MEDLINE, Scopus, CINAHL PLUS, African Index Medicus, African Journals Online, and Web of Science) and included randomised trials and quasi-experimental studies. We extracted target behaviours and specified the behavioural interventions using the Action, Actor, Context, Time, and Target (AACTT) framework. We categorised the behaviour change strategies using the intervention functions described in the Behaviour Change Wheel (BCW). We reviewed 52 articles (26 randomized trials and 26 quasi-experimental studies). They had a mixed risk of bias. Out of these, 41 studies (78.8%) targeted behaviour change of those accessing maternal healthcare services, while seven studies (13.5%) focused on those delivering maternal healthcare. Four studies (7.7%) targeted mixed stakeholder groups. The studies employed a range of behaviour change strategies, including education 37 (33.3%), persuasion 20 (18%), training 19 (17.1%), enablement 16 (14.4%), environmental restructuring 8 (7.2%), modelling 6 (5.4%) and incentivisation 5 (4.5%). No studies used restriction or coercion strategies. Education was the most common strategy for changing the behaviour of those accessing maternal healthcare, while training was the most common strategy in studies targeting the behaviour of those delivering maternal healthcare. Of the 52 studies, 40 reported effective interventions, 7 were ineffective, and 5 were equivocal. A meta-analysis was not feasible due to methodological and clinical heterogeneity across the studies. In conclusion, there is evidence of effective behaviour change interventions targeted at those accessing and/or delivering maternal healthcare in sub-Saharan Africa. However, more focus should be placed on behaviour change by those delivering maternal healthcare within the health facilities to fast-track the reduction of the huge burden of avoidable maternal deaths in sub-Saharan Africa.

There is wide variation in measures of maternal deaths, such as maternal mortality ratios (MMRs) between and within countries, but it is unclear what might be driving this variation [7].Although systematic review evidence established that the percentage of skilled birth attendance and type of hospital accounted for 44% of the total variation of the hospital MMR in sub-Saharan Africa, a greater proportion (56%) remains unexplained [8].We postulate that one explanatory factor may be differences in behaviours of those accessing and/or delivering maternal healthcare [9,10].
The behaviour of any stakeholder may influence the delivery of maternal healthcare and outcomes either positively or negatively.Examples of stakeholders include government officials, donors, multilateral partners, civil society, the private sector, local communities, community leaders, managers, auxiliary healthcare workers, women, their partners, and their families [11][12][13].Three categories of stakeholder human behaviour may influence health outcomes, and these include behaviours that contribute to disease prevention (e.g.participation in screening programmes, behaviours that involve care-seeking and adherence to treatment (e.g.antibiotic therapy and behaviours that relate to the delivery of healthcare (e.g.evidence-based practices) [14,15].
Within maternal health, some behaviours by those delivering care may enable improved outcomes (e.g., treating those accessing care with dignity).However, other behaviours like abuse and mistreatment of those seeking maternal healthcare services may contribute to suboptimal maternal health outcomes [9,15,16].
Similarly, the behaviour of those accessing maternal healthcare may influence their engagement with healthcare advice and obstetric and general health outcomes [10,17].Therefore, incorporating strategies that encourage positive behaviours and evidence-based practices while discouraging negative behaviours and discontinuing potentially harmful clinical practices is essential for enhancing maternal health outcomes and addressing avoidable maternal mortality [15].
Human behaviour and behaviour change are central to the uptake of evidence-based interventions [18,19].We postulate that the successful implementation of the current global strategy for ending avoidable maternal mortality depends on the supportive behaviour of all the stakeholders in the maternal healthcare system [20].The key focus of the strategy is on health system strengthening, addressing inequities in access, ensuring universal health coverage, addressing all the causes of maternal deaths and their contributing factors, and increasing country ownership, funding and sustainability-they all in one way or another require behaviour change for their effective implementation [20].
Therefore, there is a need first to identify and synthesise existing knowledge of behaviour change interventions for improving maternal health outcomes in sub-Saharan Africa.The identification and synthesis will provide a basis for describing existing interventions, identifying gaps in research and evidence that can be addressed through future research, informing current and future intervention development, and generating recommendations for policy and practice.
This systematic review aims to identify interventions to improve maternal health outcomes in sub-Saharan Africa through behaviour change and specify the behaviours and actors targeted by interventions and associated behaviour change strategies.As the stakeholders in maternal healthcare are potentially diverse, it is essential to specify whose and which behaviours have been targeted in existing interventions [12,13].The Action, Actor, Context, Target, and Time (AACTT) framework is a valuable tool for clarifying the behaviours of stakeholders across multiple levels of the healthcare system [21].In addition, given that behaviour change interventions are typically complex, comprising multiple interacting components, there is a need to specify what these are as a basis for describing what has been done before and what works or does not work [22].
To facilitate this work, we adopted the following definitions of behaviour and behaviour change intervention for this systematic review: • Behaviour: "Anything a person does in response to internal or external events.Actions may be overt (motor or verbal) and directly measurable or covert (activities not viewable but involving voluntary muscles) and indirectly measurable; behaviours are physical events that occur in the body and are controlled by the brain" [23].
• Behaviour change intervention: "Coordinated sets of activities designed to change specified behaviour patterns" [24].Examples include education, persuasion, incentivisation, coercion, training, enablement, modelling, environmental restructuring and restrictions We set out to answer the following research questions: 1).Which and whose behaviours are targeted by existing behaviour change interventions for improving maternal health outcomes in sub-Saharan Africa?2).Which types of behaviour change intervention strategies are currently used for improving maternal health outcomes in sub-Saharan Africa?3).What is the outcome of behaviour change intervention strategies for improving maternal health outcomes in sub-Saharan Africa?

Protocol and guidance
This systematic review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [25].The PRISMA checklist is presented in S3 Table .The protocol of this study was registered with PROSPERO (registration number CRD42022315130) [26].

Eligibility criteria
Inclusion criteria.We included randomised trials and quasi-experimental studies that were published after the launch of the Safe Motherhood Initiative in 1987 and that had the following characteristics: A population was made up of actors or stakeholders whose behaviour could influence a maternal health outcome; examples include patients, partners, health workers, families, communities, managers, and policy experts; Studies whose behaviour change intervention strategies aimed at changing the behaviour of at least one of the aforementioned stakeholder groups in the context of maternal health outcomes in sub-Saharan Africa.Examples of intervention functions are as defined in the Behaviour Change Wheel.They include education, persuasion, incentivisation, coercion, training, enablement, modelling, environmental restructuring, and restrictions [24].See Fig 1.
Exclusion criteria.We excluded articles that described behaviour (i.e.measured or assessed patterns of current practice or behaviour) or influences on behaviour (e.g.qualitative surveys or observational studies) but did not try to change the behaviour.In addition, expert opinions, commentaries, and articles that did not report the effect of the behavioural intervention were excluded.
Search strategy.We searched ten electronic databases systematically.These databases were PsycINFO, Cochrane Database of Systematic Reviews, International Bibliography of Social Sciences, EMBASE, MEDLINE, Scopus, CINAHL PLUS, African Index Medicus, African Journals Online, and Web of Science without any language restriction.We also conducted hand searches in key journals reporting behaviour change interventions, specifically the Annals of Behavioural Medicine, Health Psychology, Implementation Science, and Social Science and Medicine.
The search strategy included terms related to the following categories: Population (e.g., pregnant women, health care workers), concept (e.g., behaviour), behaviour change intervention, context description (e.g., an individual country name such as Kenya) and study design (e.g., trial, quasi-experimental).We used the intervention functions outlined in the Behaviour Change Wheel (BCW): Education, persuasion, incentivisation, coercion, training, enablement, modelling, environmental restructuring and restrictions to generate search terms related to different behaviour change strategies [24].We combined the main search terms and their synonyms using the Boolean operator "OR."We combined the descriptor categories using the Boolean operator "AND."The initial search was completed on 14 th March 2022 and updated on 11 th August 2022.Our search strategy is in S1 Table.
Article processing and study selection.We exported all the retrieved articles into End-Note version 20 (Clarivate, Philadelphia, PA, USA), a reference management software [27].After collation, we uploaded all the articles onto Covidence (Covidence, Melbourne, Australia), a systematic review management software for deduplication and article screening [28].
The eligibility criteria were piloted-tested by FGM and RG on a random sample of ten articles.FGM and RG independently screened the articles in two stages: title and abstract and fulltext screening.Discrepancies were resolved by discussion between them or with a third reviewer.

Data extraction
Data were extracted from the included studies by two reviewers (FGM and RG) independently using a pre-tested data extraction Google form (Google LLC, Mountain View, California, United States).Discrepancies were resolved by discussion between FGM and RG or with a third reviewer.
The data extraction categories included study characteristics (year of publication, first author, country, title, study design, aim, setting, sample size and duration), intervention descriptions, including recipients, providers and content, and study outcomes.The completed data extraction form and coding process are presented in supplementary files: S1 and S2 Data.

Quality assessment
We used the Joanna Briggs critical appraisal tools for randomised controlled trials and quasiexperimental studies to assess the quality of the included studies [29].Each tool was modified to provide a score of 1 for each domain, giving a maximum quality score of 13 for randomised controlled trials and 9 for quasi-experimental studies.Two reviewers (FGM and RG) independently assessed the quality of the included studies and agreed on a final score by consensus.We used the Robvis generic template and online software to generate a risk of bias plot [30]

Data synthesis
To answer research question 1 regarding whose and which behaviours were targeted, intervention descriptions were coded using the Action, Actor, Context, Target, and Time (AACTT) framework for specifying target behaviours in behaviour change interventions [21,31].This framework was previously used in systematic reviews to specify target behaviours, such as describing interventions to improve antibiotic prescribing in long-term care facilities [32].
Two reviewers, RG and FM, independently extracted, coded and synthesised the behaviour change strategies according to the intervention functions outlined in the Behaviour Change Wheel (BCW) [24].Conflicts were discussed and resolved by consensus between RG and FM.A behavioural scientist (GF) reviewed the extractions to check agreement with the AACTT coding and the BCW intervention function coding.We assessed the inter-coder reliability (RG vs FM) using Cohen's kappa (abstract and full-text screening process) and the percentage agreement across the five domains of the AACTT framework and the intervention function domain of the Behaviour Change Wheel (data extraction and coding).
We compared the types of intervention functions and target behaviour, target population and maternal health outcomes.In addition, we compared behaviour change strategies between those accessing and/or delivering maternal healthcare.
We explored all randomised trials and quasi-experimental studies for inclusion in a metaanalysis.However, a metanalysis was not feasible due to methodological and clinical diversity in aspects of the included studies' populations, interventions, comparisons, and outcomes (PICO).

Deviation from protocol
We used the Joanna Briggs tools to assess the quality of randomised trials and quasi-experimental studies [29].This deviated from the ROBINS-I tool we had proposed in our protocol (PROSPERO registration number CRD42022315130), as we anticipated that only non-randomised interventional studies would be included [26].

Results
As outlined in the PRISMA flow chart, this systematic search yielded 18549 articles, of which 15940 remained after deduplication.A further 15286 articles were excluded during the title and abstract screening process.The full texts of the remaining 653 articles were eligible for screening.Ten full-text articles were irretrievable, and 591 were ineligible for inclusion.Fiftytwo (52) articles were eligible for inclusion in the analysis.This included 26 randomised trials  and 26 quasi-experimental studies .The article identification and selection process and output are summarised in the PRISMA Flow Chart.See Fig 2.

Inter-rater reliability and quality of included studies
The inter-rater (FM and RG) reliability during the title, abstract, and full-text screening stages was calculated automatically by the Covidence systematic review management software as Cohen's kappa of 0.18597 and 0.88496, respectively.The agreement between the coders (FM and RG) across the domains of the AACTT framework was an average of 88.4%.The extent of the agreement distribution was as follows: Action 82.3%, Actor 90.4%, Context 98.1%, Target 84.6%,Time frame 98.1% and Intervention strategy 76.9%.
The quality assessment output and risk of bias chart are presented in S2 The risk of bias chart illustrates the assessment of the risk of bias of included articles across seven domains.Thirty had a high risk of bias, 12 were unclear, and 10 had a low risk of bias.The ROBVIS generic dataset is presented in S3 Data.
We identified and categorised various target behaviours into those accessing and/or delivering maternal healthcare and mixed target behaviours.The list of target behaviours is summarised in Table 1.
The target behaviours were extracted and described under the five domains of the Action, Actor, Context, Target, Time (AACTT) framework [21].The action was specified in 52 (100%) We identified various behaviour change intervention strategies used either singly or in combination.The scope of behaviour change strategies we identified is tabulated in Table 3 and ranked by frequency in Fig 4 .In studies targeting behaviour change of stakeholders accessing maternal healthcare, education was the most frequently employed strategy, while training was most commonly utilized in studies targeting behaviour change of stakeholders delivering maternal healthcare.However, there was an overlap in the choice of behaviour change strategies between the two stakeholder groups.
A comparison of behaviour change strategies by category of target stakeholder is presented in

Research question (RQ) 3: What is the outcome of behaviour change intervention strategies for improving maternal health outcomes in sub-Saharan Africa?
The behaviour change intervention strategies were reported as effective in 40 studies, ineffective in 7 and equivocal in 5.
Effective behaviour change interventions amongst those delivering maternal healthcare targeted the following behaviours: Managing disrespectful and abusive behaviours [68,77], managing obstetric emergencies confidently [48], community healthcare worker professional behaviour [50], respectful behaviour amongst professional colleagues [80], teamwork and communication behaviours [78] and supporting women to adopt healthy behaviours in antenatal care [54].
Effective behaviour change interventions with mixed targets (both those accessing and delivering maternal health care) targeted two behaviours: Promotion of respectful maternity care [73,74,83] and partner support during and after pregnancy and malaria prevention behaviour in maternal healthcare delivery [62].
Ineffective behaviour change interventions all targeted those accessing maternal healthcare.They included HIV postpartum adherence to treatment [45,55,57], intimate partner violence [46], maternal depression [79] and adoption of healthy behaviours [72,84].It is not clear why these interventions were ineffective.
Equivocal outcomes following behaviour change interventions were reported for maternal healthcare seeking [36,58], adoption of healthy behaviours [63], adherence to the prevention

Discussion
According to our knowledge, this is the only systematic review that broadly explores and presents an overview of the landscape of behavioural interventions for improving maternal health outcomes in sub-Saharan Africa.Our objective was to extract and synthesise the target behaviours, component behaviour change strategies and outcomes of behaviour change interventions for improving maternal health outcomes in sub-Saharan Africa.We found mixed-quality evidence from randomised trials and quasi-experimental studies conducted in 12 sub-Saharan Africa countries: Kenya, Ethiopia, South Africa, Malawi, Ghana, Nigeria, Egypt, Zambia, Uganda, Rwanda, the Democratic Republic of Congo, and the United Republic of Tanzania.Using the Joanna Briggs tools to assess the quality of randomised trials and quasi-experimental studies, we found that most included studies had either a high (30 studies) or uncertain (12 studies) risk of bias.Only ten studies had a low risk of bias.
Scholars have reported in reviews that behavioural studies carry a high risk of bias, and it remains unclear whether this results from methodological flaws, reporting issues, or a mismatch of existing quality assessment tools to behavioural studies [85].Tools such as the risk of bias justification table (RATIONALE) were designed to improve the quality of the conduct, reporting and assessment of behavioural trials [86].It is crucial to consider our systematic review findings in light of the risk of bias categories we reported and the tool we utilised for quality assessment.So far, behaviour change interventions have focused mainly on those accessing maternal health services compared to those responsible for delivering the services within the health facilities.This skewed focus can partly be explained by the years of investment in efforts to encourage women to access maternal healthcare services and deliver under-skilled birth attendance [87].However, despite more women coming to deliver within healthcare facilities, there has been concern regarding the quality of healthcare delivery contributing to suboptimal outcomes, including avoidable maternal deaths [88].
Multiple factors, such as suboptimal service delivery, contribute to suboptimal maternal health outcomes, with some being due to the attitude and behaviours of those delivering maternal health care [10].Indeed, systematic review evidence published in 2015 documented a broad range of negative attitudes and behaviours by those delivering maternal healthcare that affect patient well-being, care satisfaction and care seeking [9].
Education of those accessing maternal health services and training those delivering maternal healthcare were the leading behaviour change strategies in our systematic review.This finding was similar to a scoping review on approaches for changing behaviour in pregnant women that found the educational approach to be the dominant strategy [89].
Quite often, education and training were used in combination with other strategies.Combining intervention strategies is a common practice, as reported in a 2017 Cochrane review on psychosocial interventions for supporting women to stop smoking during pregnancy [90].Among healthcare workers, an overview of systematic reviews published in 2015 found that bundles of professional behaviour change interventions in healthcare seemed more effective when packaged together than as a single intervention [91].
The finding of training as the dominant intervention strategy, compared to other behaviour change intervention strategies, can be partially elucidated by the "failure to rescue" concept.The concept describes a failure or delay in recognizing and responding to patient deterioration, leading to morbidity or mortality [92].
In an attempt to mitigate against failure to rescue, it is assumed that a lack of or outdated training is the cause.As a result, the training of healthcare workers is often prioritised over other elements in the healthcare system, such as organisational, environmental, people, tasks, technology and tools factors that may equally impact healthcare delivery and outcomes [93,94].
Although most behavioural interventions were effective, a few had either ineffective or equivocal outcomes.We did not determine the reasons for the ineffective or equivocal outcomes.However, evidence from the field of behavioural science suggests that the outcome of a behaviour change intervention is influenced by a variety of methodological and contextual factors [14,95].We postulate that methodological flaws and contextual factors may explain the failure of behavioural interventions to achieve the desired outcomes.

Interpretation of the findings
There is evidence of using a range of behaviour change approaches to improve maternal health outcomes in some countries in sub-Saharan Africa.A greater proportion of previous interventions targeted those accessing maternal healthcare services compared to those delivering the services.This is important because current evidence suggests that the quality of care within healthcare facilities ought to be a focus of initiatives aimed at improving maternal health outcomes, including tackling avoidable maternal deaths.
Regarding the scope of focus: Existing behavioural interventions focus on tackling challenges relating to human factors in service delivery, such as respectful care and teamwork.None of the studies focused on behavioural change aspects of managing specific obstetric conditions, such as obstetric haemorrhage, sepsis, hypertensive disorders, unsafe abortion, and obstructed labour, which are the leading causes of direct maternal deaths in sub-Saharan Africa.
Finally, although some behaviour change interventions were successful, it is essential to consider other context-specific factors that may influence external validity and scalability at other health facilities, regions, or countries.

Strengths and limitations
The main strength of our systematic review is the novel use of innovative behavioural science frameworks (AACTT framework and BCW) to synthesise our findings with the effect of providing depth and clarity in categorising behaviours and intervention strategies.In addition, our systematic review provides a comprehensive overview of the behavioural interventions landscape in maternal health and the sub-Saharan Africa context.The comprehensive scope was aided by a robust search strategy and a wide variety of article sources focussing on sub-Saharan Africa, including from Africa-focused databases.The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed in our systematic review to ensure consistency in reporting.The PRISMA checklist is presented in S3 Table.
Our systematic review has several limitations.First, most included studies exhibited a high or uncertain risk of bias, potentially impacting the reliability of findings.This finding of moderate to high risk of bias is not unexpected in behaviour change interventional studies [85].Behavioural scientists acknowledge biases that may affect behaviour change intervention studies, such as performance and contamination bias, and advise adopting methodological strategies to mitigate against biases [86].Second, our choice of a narrative over quantitative synthesis meant that we could not establish the effect size of the strength of the effectiveness of the interventions.Finally, while we found evidence of effective behaviour change interventions, which could indirectly lead to a decrease in avoidable maternal deaths, a limitation is that none of the interventions directly correlated behaviour change with a reduction in the maternal mortality rate.

Implications for maternal healthcare workers, policymakers, and governments in sub-Saharan Africa
There is a need to recognise the currently underused potential of behaviour change approaches to improve maternal health outcomes.Despite shared challenges in tackling maternal health problems, some health facilities, regions, or countries may perform better than others due to unique, effective behaviours and practices.
If identified, these unique practices and behaviours can then be decentralised from the highperforming health facilities through knowledge sharing, leading to positive change in outcomes in the poorly performing health facilities.The overall impact of embracing behavioural interventions in conjunction with existing strategies may be an improvement in maternal health outcomes and a faster reduction in the burden of avoidable maternal deaths in sub-Saharan Africa.

Suggestions for future research
Our systematic review identified research and practice gaps which could inform future research.First, the high number of articles with a high and uncertain risk of bias indicates a need to conduct further research towards improving behaviour change research methodology.Second, behaviour change implementation researchers at health facilities or regions with high maternal mortality should consider assessing the direct impact of the behaviour change intervention on maternal mortality rate.We acknowledge that this may be a challenge to investigate at health facilities or regions where maternal deaths are a rare occurrence.Third, as most interventions have been pre-hospital and involving those accessing healthcare, there is a need for future research to explore targeting behaviours and their influencing factors related to maternal health outcomes at the health facility level.Specifically, the identification of the challenges that healthcare workers face and how they modify their practices and behaviour to achieve better maternal health outcomes.If unique mitigation practices and behaviours are identified at a health facility, they could be explored for the feasibility of solving similar challenges nearby health facilities face, therefore, improving maternal health outcomes by overcoming local challenges with local shared solutions.

Conclusion
Although more research is required to improve the scope and methodological quality of the current evidence base, behaviour change interventions targeted at those accessing and/or delivering maternal healthcare exist and may have a role in improving maternal health outcomes and tackling avoidable maternal deaths in Sub-Saharan Africa.They should be reviewed for incorporation into existing strategies for improving maternal health outcomes and tackling the causes of avoidable maternal deaths.
There is evidence of effective behaviour change interventions targeted at those accessing and/or delivering maternal healthcare in sub-Saharan Africa.However, more focus should be placed on behaviour change by those delivering maternal healthcare within the health facilities to fast-track the reduction of the huge burden of avoidable maternal deaths in sub-Saharan Africa.

Fig 2 .
Fig 2. PRISMA flow chart.The flow chart illustrates the output from the article identification and selection process, namely: Identification, title and abstract screening, and full-text screening for eligibility (both exclusion and inclusion).

Fig 3 .
Fig 3. Risk of bias chart.This Robvis generated chart presents the quality assessment across seven domains summarised into three categories: "X" represents a high risk of bias, "-"represents an unclear risk of bias and "+" represents a low risk of bias.https://doi.org/10.1371/journal.pgph.0002950.g003 Fig 5.

Fig 5 .
Fig 5. Behaviour change strategies relationship map.Those accessing maternal healthcare (biggest circle), those delivering maternal healthcare (medium circle) and mixed targets (smallest circle).The thickened lines illustrate more than one strategy.Various behaviour change strategies, exclusively or in combination, were utilised with some overlap.https://doi.org/10.1371/journal.pgph.0002950.g005